pois_sgp: Sparse Gaussian process for Poisson data via variational...

In DongyueXie/smashrgen: Empirical Bayes smoothers

Sparse Gaussian process for Poisson data via variational inference

Description

Sparse Gaussian process for Poisson data via variational inference

Usage

pois_sgp(
  y,
  sc = NULL,
  X = NULL,
  X_ind = NULL,
  m = 30,
  kernel_func = Maternkernel,
  kernel_param = NULL,
  mu = NULL,
  post_mean = NULL,
  V = NULL,
  opt_method = "L-BFGS-B",
  fix_X_ind = T,
  fix_kernel_param = F,
  fix_mu = F,
  maxiter = 100,
  tol = 1e-05,
  maxiter_mean = 100,
  tol_mean = 1e-05,
  maxiter_V = 100,
  tol_V = 1e-05,
  Jitter = 1e-05,
  verbose = T,
  printevery = 1
)

Arguments

y	count vector
sc	scaling scalar or vectors
X, X_ind	grids, and inducing points
m	number of inducing points
kernel_func, kernel_param	functions and their parameters
post_mean, V	posterior mean and var of f at inducing point

DongyueXie/smashrgen documentation built on Jan. 14, 2024, 5:30 a.m.